Processing System for Dynamic Collison Verification &amp; Sensor Selection

ABSTRACT

Aspects of the disclosure relate to computing platforms that utilize improved techniques for dynamic event verification and sensor selection. A computing platform may determine accuracy for each of a plurality of sensor devices for each of a plurality of data types. For each of the data types, the computing platform may rank the plurality of sensor devices based on their corresponding accuracy. The computing platform may direct a first sensor device and a second sensor device to provide first and second source data respectively. These sensor devices may be the most accurate sources of data types corresponding to the first and second source data respectively. The computing platform may receive the first source data and the second source data. Based on the first source data and the second source data, the computing platform may generate an event output indicating whether a vehicle experienced an event.

BACKGROUND

Aspects of the disclosure relate to enhanced processing systems forperforming dynamic event verification and sensor selection. Manyorganizations and individuals rely on sensor data to determine whetheran event occurred. In many instances, however, data used to determinewhether an event occurred, or the determinations themselves may beinaccurate. There remains an ever-present need to develop improvedmethods of verifying whether an event occurred using sensor data.

SUMMARY

Aspects of the disclosure provide effective, efficient, scalable, andconvenient technical solutions that address and overcome the technicalproblems associated with event verification and sensor selection. Inaccordance with one or more arrangements discussed herein, a computingplatform having at least one processor, a communication interface, andmemory may access a sensor capability database to determine an accuracyoutput associated with each of a plurality of sensor devices for each ofa plurality of data types. For each of the data types and based on theiraccuracy outputs, the computing platform may rank the plurality ofsensor devices, resulting in a ranked list of the plurality of sensordevices. The computing platform may send one or more commands directinga first sensor device to provide first source data and directing asecond sensor device to provide second source data. The first sensordevice may be ranked highest on the ranked list of the plurality ofsensor devices for a data type corresponding to the first source dataand the second sensor device may be ranked highest on the ranked list ofthe plurality of sensor devices for a data type corresponding to thesecond source data. The computing platform may receive, from the firstsensor device and the second sensor device respectively, the firstsource data and the second source data. Based on the first source dataand the second source data, the computing platform may generate an eventoutput indicating whether a vehicle associated with the first sourcedata and the second source data experienced an event.

In some examples, the computing platform may establish a wirelessconnection with a geographic policy database. While the wirelessconnection is established and after ranking the plurality of sensordevices, the computing platform may send one or more commands directingthe geographic policy database to provide an indication of whether useof the first sensor device complies with geographic policies. While thewireless connection is established, the computing platform may receivethe indication of whether use of the first sensor device complies withgeographic policies.

In some arrangements, sending the one or more commands directing thefirst sensor device to provide first source data may be in response todetermining, based on the indication of whether the use of the firstsensor device complies with geographic policies, that the first sensordevice complies with geographic policies.

In some examples, while the wireless connection is established and afterranking the plurality of sensor devices, the computing platform may sendone or more commands directing the geographic policy database to providean indication of whether use of a third sensor device complies withgeographic policies. The third sensor device may be ranked highest onthe ranked list of the plurality of sensor devices for a data typecorresponding to third source data. While the wireless connection isestablished, the computing platform may receive the indication ofwhether use of the third sensor device complies with geographicpolicies. Based on the indication of whether use of the third sensordevice complies with geographic policies, the computing platform maydetermine that the third sensor device is non-compliant with thegeographic policies. After determining that the third sensor device isnon-compliant with the geographic policies, the computing platform maysend one or more commands directing the geographic policy database toprovide an indication of whether use of a fourth sensor device complieswith geographic policies. The fourth sensor device may be ranked secondhighest on the ranked list of the plurality of sensor devices for thedata type corresponding to the third source data. In response todetermining, based on the indication of whether the use of the thirdsensor device complies with geographic policies, that the third sensordevice complies with geographic policies, the computing platform maysend one or more commands directing the fourth sensor device to providethe third source data.

In some arrangements, the computing platform may determine that eventanalysis should occur locally at one of the plurality of sensor devices.The computing platform may rank the plurality of sensor devices based onavailable processing power at each of the plurality of sensor devices,resulting in a ranked list of sensor devices by processing power. Thecomputing platform may send one or more commands to the first sensordevice directing the first sensor device to determine the event output.The first sensor device may be the highest ranked device on the rankedlist of sensor devices by processing power.

In some examples, the computing platform may determine that eventanalysis should occur at the computing platform. In some examples,determining the event output may be in response to determining that theevent analysis should occur at the computing platform.

In some arrangements, determining the event output may comprisedetermining, using one or more machine learning algorithms and one ormore machine learning datasets, an indication of whether the vehicleexperienced an event. In some arrangements, the computing platform mayestablish a wireless connection with an event assistance platform. Whilethe wireless connection is established and to the event assistanceplatform, the computing platform may send the event output and one ormore commands directing the event assistance platform to cause displayof the event output.

These features, along with many others, are discussed in greater detailbelow.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure is illustrated by way of example and not limitedin the accompanying figures in which like reference numerals indicatesimilar elements and in which:

FIGS. 1A-1B depict an illustrative computing environment for deployingcomputing platforms that utilize improved event verification and sensorselection techniques in accordance with one or more example arrangementsdiscussed herein;

FIGS. 2A-2C depict an illustrative event sequence for deployingcomputing platforms that utilize improved event verification techniquesin accordance with one or more example arrangements discussed herein;

FIGS. 3A-3E depict an illustrative event sequence for deployingcomputing platforms that utilize improved sensor selection techniques inaccordance with one or more example arrangements discussed herein;

FIGS. 4 and 5 depict illustrative methods for deploying computingplatforms that utilize improved event verification and sensor selectiontechniques in accordance with one or more example arrangements discussedherein; and

FIGS. 6 and 7 depict illustrative user interfaces for computingplatforms that utilize improved event verification and sensor selectiontechniques in accordance with one or more example arrangements discussedherein.

DETAILED DESCRIPTION

In the following description of various illustrative embodiments,reference is made to the accompanying drawings, which form a parthereof, and in which is shown, by way of illustration, variousembodiments in which aspects of the disclosure may be practiced. It isto be understood that other embodiments may be utilized, and structuraland functional modifications may be made, without departing from thescope of the present disclosure.

It is noted that various connections between elements are discussed inthe following description. It is noted that these connections aregeneral and, unless specified otherwise, may be direct or indirect,wired or wireless, and that the specification is not intended to belimiting in this respect.

As a brief summary, the present disclosure provides systems and methodsfor increasing accuracy of event determinations and selecting sensorsfor data collection based on their capabilities. In one or moreinstances, the events may include a collision, sudden movement, harshbreaking, rollover, or the like. In one or more instances, sensordevices may effectively peer across to confirm determinations and/orsource data with another sensor device. In these instances, the sensordevices may communicate via a central event analysis platform or theymay communicate directly with each other. In doing so, the sensordevices may provide verified source data and/or determinations ofwhether an event occurred, which may be more accurate than instances inwhich the sensor devices did not communicate. Additionally oralternatively, source data may be collected from multiple differentsensors and used in an overall determination of whether a vehicleexperienced an event. Certain sensors may be more accurate atdetermining particular types of data than others. Accordingly, byselecting particular sensors to provide a particular type of data,accuracy of the data collection may be maximized. By obtaining the mostaccurate source data, more accurate determinations of whether or not avehicle experienced an event may occur. Accordingly, by applying themethods described herein, determination of whether or not a vehicleexperienced an event, using source data from various sensor devices, maybe improved. This may reduce an amount of false determinations ofwhether a vehicle was or was not involved in an event, which mayconserve resources by not responding to false positive determinationsand may improve driving safety by ensuring that responders are notifiedand dispatched when an event actually occurs (e.g., rather than beinginformed of a false negative determination). These and various otherarrangements will be described more fully herein.

FIGS. 1A and 1B depict an illustrative computing environment forperforming advanced dynamic event verification and sensor selection inaccordance with one or more example embodiments. Referring to FIG. 1A,computing environment 100 may include one or more computer systems. Forexample, computing environment 100 may include event analysis and sensorcontrol platform 102, first sensor device 103, second sensor device 104,geographic policy database 105, and event assistance platform 106.

As illustrated in greater detail below, event analysis and sensorcontrol platform 102 may include one or more computing devicesconfigured to perform one or more of the functions described herein. Forexample, event analysis and sensor control platform 102 may include oneor more computers (e.g., laptop computers, desktop computers, servers,server blades, or the like). In one or more instances, event analysisand sensor control platform 102 may be configured to receive datacaptured by the sensor devices 103 and 104 and analyze the data todetermine whether a vehicle experienced an event. In one or moreinstances, the event analysis and sensor control platform 102 may alsobe configured to determine a most accurate data source for particulardata types, collect source data from these different sources, anddetermine, based on a combination of the source data from differentsources, whether a vehicle experienced an event.

As illustrated in greater detail below, the event analysis and sensorcontrol platform 102 may be configured to generate, host, transmit,and/or otherwise provide one or more web pages and/or other graphicaluser interfaces (which may, e.g., cause one or more other computersystems to display and/or otherwise present the one or more web pagesand/or other graphical user interfaces). In some instances, the webpages and/or other graphical user interfaces generated by event analysisand sensor control platform 102 may be associated with an externalportal provided by an organization, such as event management interfacesthat provide warnings and/or prompt users to confirm whether an eventoccurred.

First sensor device 103 may be a computing device configured to collectand send data for further analysis. In some instances, first sensordevice 103 may be a personal computing device (e.g., smartphone, laptopcomputer, desktop computer, tablet computer, or the like) that iscapable of receiving commands and generating user interfacesaccordingly. In addition, first sensor device 102 may include one ormore cameras and/or sensors (e.g., motion sensors, global positioningsensors, temperature sensors, microphones or the like) that may be usedto capture data corresponding to a driving trip. In some instances, thefirst sensor device 103 may be configured to send this data upon requestor at predetermined intervals for analysis. Additionally oralternatively, the first sensor device 103 may be a vehicle sensor(e.g., speedometer, accelerometer, break detection systems, impactsensors, airbag deployment sensors, cameras, or the like). In one ormore instances, the first sensor device 103 may be configured to requestconfirmation source data from a second sensor device (e.g., secondsensor device 104). Additionally or alternatively, the first sensordevice 103 may be configured to send the source data to the eventanalysis and sensor control platform 102, which may request theconfirmation source data. In one or more instances, the first sensordevice 103 may be configured to analyze determined and/or receivedsource data to determine whether an event occurred.

Second sensor device 104 may be a computing device configured to collectand send data for further analysis. In some instances, second sensordevice 104 may be a personal computing device (e.g., smartphone, laptopcomputer, desktop computer, tablet computer, or the like) that iscapable of receiving commands and generating user interfacesaccordingly. In addition, second sensor device 104 may include one ormore cameras and/or sensors (e.g., motion sensors, global positioningsensors, temperature sensors, microphones or the like) that may be usedto capture data corresponding to a driving trip. In some instances, thesecond sensor device 104 may be configured to send this data uponrequest or at predetermined intervals for analysis. Additionally oralternatively, the second sensor device 104 may be a vehicle sensor(e.g., speedometer, accelerometer, break detection systems, impactsensors, airbag deployment sensors, cameras, or the like). In one ormore instances, the second sensor device may be configured to requestconfirmation source data from another sensor device (e.g., first sensordevice 103). Additionally or alternatively, the second sensor device 104may be configured to send the source data to the event analysis andsensor control platform 102, which may request the confirmation sourcedata. In one or more instances, the second sensor device 104 may beconfigured to analyze determined and/or received source data todetermine whether an event occurred.

Geographic policy database 105 may be a computing platform capable ofstoring and maintaining various information corresponding to one or moresensor use policies. For example, the geographic policy database 105 maycontain data corresponding to which sensors may legally collect data invarious geographic regions (e.g., different states, countries, or thelike). In these instances, the data may be collected after receivingappropriate permissions from a user. In one or more instances, thegeographic policy database 105 may be configured to receive requests forwhether particular sensor devices (e.g., first sensor device 103, secondsensor device 104, or the like) are compliant with data collectionpolicies in a particular region. The geographic policy database 105 maydetermine whether the requested sensor devices are compliant, and maygenerate/send an indication to the event analysis and sensor controlplatform 102 indicating whether or not the requested sensor devices arecompliant.

Event assistance platform 106 may be a computing device (e.g., a desktopcomputer, laptop computer, tablet computer, smart phone, or the like)that may be used to receive event indications and generate userinterfaces and/or dispatch requests accordingly. For example, the eventassistance platform 106 may receive an indication of an event and maygenerate user interfaces to indicate details of the event to an employeeof an institution. Additionally or alternatively, the event assistanceplatform 106 may automatically generate a dispatch request to sendassistance to the location of the event.

Computing environment 100 also may include one or more networks, whichmay interconnect one or more of event analysis and sensor controlplatform 102, first sensor device 103, second sensor device 104,geographic policy database 105, and event assistance platform 106. Forexample, computing environment 100 may include a network 101 (which may,e.g., interconnect event analysis and sensor control platform 102, firstsensor device 103, second sensor device 104, geographic policy database105, and event assistance platform 106).

In one or more arrangements, event analysis and sensor control platform102, first sensor device 103, second sensor device 104, geographicpolicy database 105, event assistance platform 106, and/or the othersystems included in computing environment 100 may be any type ofcomputing device capable of receiving a user interface, receiving inputusing the user interface, and communicating the received input to one ormore other computing devices. For example, event analysis and sensorcontrol platform 102, first sensor device 103, second sensor device 104,geographic policy database 105, event assistance platform 106, and/orthe other systems included in computing environment 100 may, in someinstances, be and/or include server computers, desktop computers, laptopcomputers, tablet computers, smart phones, sensors, or the like that mayinclude one or more processors, memories, communication interfaces,storage devices, and/or other components. As noted above, and asillustrated in greater detail below, any and/or all of event analysisand sensor control platform 102, first sensor device 103, second sensordevice 104, geographic policy database 105, and event assistanceplatform 106 may, in some instances, be special-purpose computingdevices configured to perform specific functions.

Referring to FIG. 1B, event analysis and sensor control platform 102 mayinclude one or more processors 111, memory 112, and communicationinterface 113. A data bus may interconnect processor 111, memory 112,and communication interface 113. Communication interface 113 may be anetwork interface configured to support communication between mitigationanalysis and output generation platform 103 and one or more networks(e.g., network 101, or the like). Memory 112 may include one or moreprogram modules having instructions that when executed by processor 111cause event analysis and sensor control platform 102 to perform one ormore functions described herein and/or one or more databases that maystore and/or otherwise maintain information which may be used by suchprogram modules and/or processor 111. In some instances, the one or moreprogram modules and/or databases may be stored by and/or maintained indifferent memory units of event analysis and sensor control platform 102and/or by different computing devices that may form and/or otherwisemake up event analysis and sensor control platform 102. For example,memory 112 may have, store, and/or include an event analysis and sensorcontrol module 112 a, an event analysis and sensor control database 112b, and a machine learning engine 112 c. Event analysis and sensorcontrol module 112 a may have instructions that direct and/or causeevent analysis and sensor control platform 102 to execute advanced eventanalysis and sensor control techniques, as discussed in greater detailbelow. Event analysis and sensor control database 112 b may storeinformation used by event analysis and sensor control module 112 aand/or event analysis and sensor control platform 102 in event analysis,sensor selection, sensor control, and/or in performing other functions.Machine learning engine 112 c may have instructions that direct and/orcause the event analysis and sensor control platform 102 to performevent analysis, sensor selection, and sensor control, and to set,define, and/or iteratively refine optimization rules and/or otherparameters used by the event analysis and sensor control platform 102and/or other systems in computing environment 100.

FIGS. 2A-2C depict an illustrative event sequence for deploying an eventanalysis and sensor control platform 103 that uses advanced techniquesto perform event analysis and sensor selection in accordance with one ormore example embodiments. Referring to FIG. 2A, at step 201, the firstsensor device 103 and the second sensor device 104 may collect sourcedata. In one or more instances, in collecting source data, the firstsensor device 103 and the second sensor device 104 may collecttelematics data (e.g., speed, acceleration, location, deceleration,stopping, turning, swerving, impact, or the like). Additionally oralternatively, in collecting source data the first sensor device 103 andthe second sensor device 104 may collect non-telematics data (e.g.,pictures, video, cell phone usage, audio, or the like). In one or moreinstances, in collecting the source data, the first sensor device 103and the second sensor device 104 may collect source data over apredetermined time period. In these instances, the predetermined timeperiod may be configurable by a user.

At step 202, the first sensor device 103 may establish a connection withthe event analysis and sensor control platform 102. In one or moreinstances, the first sensor device 103 may establish a first wirelessdata connection with the event analysis and sensor control platform 102to link the first sensor device 102 to the event analysis and sensorcontrol platform.

At step 203, the first sensor device 103 may send source data, collectedat step 201 by the first sensor device 103, to the event analysis andsensor control platform 102. In one or more instances, the first sensordevice 103 may send the source data to the event analysis and sensorcontrol platform 102 while the first wireless data connection isestablished. In some instances, the first sensor device 103 may send thesource data to the event analysis and sensor control platform 102 at apredetermined interval. Additionally, or alternatively, the first sensordevice 103 may send the source data to the event analysis and sensorcontrol platform 102 if the source data exceeds a predeterminedthreshold (e.g., impact detected that exceeds a predeterminedthreshold). Additionally or alternatively, the first sensor device 103may send the source data to the event analysis and sensor controlplatform 102 in response to one or more commands from the event analysisand sensor control platform 102 directing the first sensor device tosend the source data.

In one or more instances, in addition to or as an alternative tocommunicating the source data to the event analysis and sensor controlplatform 102, the first sensor device 103 may directly communicate withthe second sensor device 104. In these instances, the event analysis andsensor control platform 102 may send one or more commands to the secondsensor device 104 directing the second sensor device 104 to confirm thesource data. In these instances, the event analysis and sensor controlplatform 102 may send the source data along with the one or morecommands directing the second sensor device 104 to confirm the sourcedata.

In one or more instances, in addition to or as an alternative to sendingthe source data to the event analysis and sensor control platform 102and/or the second sensor device 104, the first sensor device 103 maydetermine, using one or more machine learning algorithms and datasets,whether the source data is indicative of an event. For example, thefirst sensor device 103 may compare the source data to one or more eventthresholds (e.g., impact exceeded a predetermined threshold, or thelike) to determine an event output indicating whether a vehicle likelyexperienced an event. In these instances, the first sensor device 103may send the event output to the event analysis and sensor controlplatform 102 and/or second sensor device 104.

At step 204, the event analysis and sensor control platform 102 mayreceive the source data sent at step 203. In one or more instances, inreceiving the source data, the event analysis and sensor controlplatform 102 may receive the source data while the first wireless dataconnection is established and via the communication interface 113. Inone or more instances, in addition to or as an alternative to, receivingthe source data, the event analysis and sensor control platform 102 mayreceive an event output from the first sensor device 103 indicatingwhether the vehicle was believed to be in an event.

In one or more instances, the source data received at step 204 might notindicate an event, but may indicate information to prevent an event forthe vehicle and/or other surrounding vehicles. For example, in one ormore instances, the source data may indicate that the vehicle isseverely braking. In these instances, the event analysis and sensorcontrol platform 102 may generate and send event management interfaceinformation to mobile devices within a predefined distance alerting themof the braking and prompting the mobile devices to generate an eventmanagement interface in response. In one or more instances, the mobiledevice may generate an event management interface similar to graphicaluser interface 605, which is shown in FIG. 6. For example, the mobiledevice may indicate that vehicles are slowing ahead and that a drivershould slow down preemptively. In these instances, the mobile device maybe located in a different vehicle than the first data source.

At step 205, the event analysis and sensor control platform 102 maydetermine an event output. For example, the event analysis and sensorcontrol platform 102 may determine, using one or more machine learningalgorithms and datasets, whether the source data is indicative of anevent. For example, the event analysis and sensor control platform 102may compare the source data to one or more event thresholds (e.g.,impact exceeded a predetermined threshold, or the like) to determine anevent output indicating whether a vehicle likely experienced an event.

In one or more instances, the event analysis and sensor control platform102 may have received the event output from the first sensor device atstep 104. In these instances, the event analysis and sensor controlplatform 102 might not determine the event output.

Referring to FIG. 2B, at step 206, the event analysis and sensor controlplatform 102 may establish a connection with the second sensor device104. In one or more instances, the second sensor device 104 may belocated in the same vehicle as the first sensor device 103. In otherinstances, the second sensor device 104 may be located in a differentvehicle than the first sensor device 103. In one or more instances, theevent analysis and sensor control platform 102 may establish a secondwireless connection with the second sensor device 104. In one or moreinstances, the event analysis and sensor control platform 102 maydetermine that a connection should be established with the second sensordevice 104 as opposed to other sensor devices based on accuracy of dataprovided by the second sensor device 104, geographic data collectionregulations, or the like. Such selection of the second sensor device 104is described further below with regard to FIGS. 3A-3E.

At step 207, the event analysis and sensor control platform 102 maygenerate one or more commands directing the second sensor device 104 toconfirm the event output and may send the one or more commands directingthe second device 104 to confirm the event output to the second sensordevice 104. In one or more instances, the event analysis and sensorcontrol platform 102 may send the one or more commands directing thesecond device 104 to confirm the event output via the communicationinterface 113 while the second wireless data connection is established.In these instances, the event analysis and sensor control platform 102may generate the one or more commands directing the second sensor device104 to confirm the event output in response to determining the eventoutput.

In one or more instances, in sending the one or more commands directingthe second sensor device 104 to confirm the event output, the eventanalysis and sensor control platform 102 may send event managementinterface information, and the one or more commands directing the secondsensor device 104 to confirm the event output may direct the secondsensor device 104 to cause display of a user interface similar tographical user interface 705, which is shown in FIG. 7. For example, asshown in FIG. 7, the second sensor device may generate a user interfaceindicating that an event was determined by the event analysis and sensorcontrol platform 102, and asking for user input to confirm. In theseinstances, the second sensor device 104 may be a mobile device or othervehicle system configured to display user interfaces and receive userinputs.

At step 208, the second sensor device 104 may receive the one or morecommands directing the second device 104 to confirm the event outputsent at step 207. In one or more instances, the second sensor device 104may receive the one or more commands directing the second device 104 toconfirm the event output while the second wireless data connection isestablished. In one or more instances, rather than receiving the one ormore commands directing the second device 104 to confirm the eventoutput from the event analysis and sensor control platform 102, thesecond sensor device 104 may receive the one or more commands directingthe second device 104 to confirm the event output directly from thefirst sensor device 103. In one or more instances, in addition to or asan alternative to receiving the one or more commands directing thesecond device 104 to confirm the event output, the second sensor device104 may receive one or more commands directing the second sensor device104 to confirm the source data determined by the first sensor device103.

At step 209, the second sensor device 104 may send confirmation of theevent input to the event analysis and sensor control platform 102. Inone or more instances, in sending the confirmation of the event outputto the event analysis and sensor control platform 102, the second sensordevice 104 may send the source data determined by the second sensordevice 104 at step 201. Additionally or alternatively, the second sensordevice 104 may analyze the source data determined by the second sensordevice 104 at step 201 to determine, using one or more machine learningalgorithms and datasets, whether the vehicle likely experienced anevent. In these instances, the second sensor device 104 may send anindication of whether or not the vehicle experienced an event to theevent analysis and sensor control platform 102 and/or the first sensordevice 103. In doing so, the first sensor device 103 may effectivelypeer across, either directly or through the event analysis and sensorcontrol platform 102, to the second sensor device 104 to confirm thedetermined source data and/or event output. For example, the firstsensor device 103 asks the second sensor device 104, “did you see what Isaw?”

At step 210, the event analysis and sensor control platform 102 mayreceive the source data and/or confirmation of the event output from thesecond sensor device 104. In one or more instances, the event analysisand sensor control platform 102 may receive the source data and/orconfirmation of the event output from the second sensor device 104 viathe communication interface 113 and while the second wireless dataconnection is established. In one or more instances, in addition to orinstead of the event analysis sensor control platform 102 receiving thesource data and/or confirmation of the event output from the secondsensor device 104, the first sensor device 103 may receive the sourcedata and/or confirmation of the event output. In one or more instances,the source data received from the second sensor device 104 may be adifferent type of data than the source data received from the firstsensor device 103. In other instances, the source data received from thesecond sensor device 104 may be the same type of data received from thefirst sensor device 103.

At step 211, the event analysis and sensor control platform 102 maycompare the source data from the first sensor device 103 and the secondsensor device 104. Additionally or alternatively, the event analysis andsensor control platform 102 may compare the event output with theconfirmation of the event output from the second sensor device 104. Inthese instances, the event analysis and sensor control platform 102 maygenerate an event comparison output, which may be a numeric valuerepresenting a correlation or similarity between the source data and/orevent outputs. In these instances, the event analysis and sensor controlplatform 102 may determine whether event comparison output exceeds apredetermined comparison threshold. If the predetermined comparisonthreshold is exceeded, the event analysis and sensor control platform102 may determine that the event output initially determined wascorrect. If the predetermined comparison threshold is not exceeded, theevent analysis and sensor control platform 102 may determine that theevent output initially determined was not correct. In one or moreinstances, the comparison performed at step 211 may be performed by thefirst sensor device 103 in addition to or instead of at the eventanalysis and sensor control platform 102. By performing this comparison,a determination that a vehicle was or was not involved in an accidentbased on source data from the first sensor device 103 may be confirmedbased on source data from the second sensor device 104. Additionally oralternatively, the source data from the first sensor device 103 itselfmay be confirmed based on the source data from the second sensor device104.

In one or more instances, if the event comparison output does exceed thepredetermined comparison threshold, the event analysis and sensorcontrol platform 102 may send event management interface information,and one or more commands directing a user's mobile device to confirmthat an event occurred. In these instances, the user may be a usercorresponding to the vehicle that experienced the event. In someinstances, the user might not be a user in the vehicle (e.g., a parentof a child, emergency contact, or the like). In these instances, theevent analysis and sensor control platform may direct the second sensordevice 104 to cause display of a user interface similar to graphicaluser interface 705, which is shown in FIG. 7. For example, as shown inFIG. 7, the mobile device may generate a user interface indicating thatan event was determined by the event analysis and sensor controlplatform 102, and asking for user input to confirm.

Referring to FIG. 2C, at step 212, the event analysis and sensor controlplatform 102 may update the machine learning engine 112 c. In one ormore instances, the event analysis and sensor control platform 102 mayupdate the machine learning engine 112 c based on a determination thatthe event output was correct (e.g., correctly determined event/noevent). In these instances, the event analysis and sensor controlplatform 102 may reinforce the machine learning algorithms and datasetsused to determine the event output based on the source data from thefirst sensor device 103. In other instances, the event analysis andsensor control platform 102 may update the machine learning engine 112 cbased on a determination that the event output was not correct (e.g.,false positive/negative). In these instances, the event analysis andsensor control platform 102 may update the machine learning algorithmsand datasets used to determine the event output to reflect that anincorrect determination was made.

At step 213, the event analysis and sensor control platform 102 mayestablish a connection with the event assistance platform 106. In one ormore instances, the event analysis and sensor control platform 102 mayestablish a third wireless data connection with the event assistanceplatform 106 to link the event analysis and sensor control platform 102to the event assistance platform 106.

At step 214, the event analysis and sensor control platform 102 maygenerate and send an indication of whether an event (e.g., a collision,sudden movement, harsh breaking, rollover, or the like) occurred to theevent assistance platform. In one or more instances, the event analysisand sensor control platform 102 may generate and send the indication ofwhether the event occurred to the event assistance platform 106 via thecommunication interface 113 and while the third wireless data connectionis established.

At step 215, the event assistance platform 106 may receive theindication of whether the event occurred. In one or more instances, theevent assistance platform 106 may generate a user interface based on theindication of whether the event occurred, alerting an employee of aninstitution (e.g., an insurance institution or the like) that an eventoccurred and that action should be taken accordingly. Additionally oralternatively, the event assistance platform 106 may automaticallygenerate and send a dispatch notification causing a service vehicle,police, ambulance, or the like to be dispatched to a location of theevent.

Subsequently the event sequence may end. It should be understood thatany or the steps performed by the event analysis and sensor controlplatform 102 may be performed by one of the first sensor device 103 andthe second sensor device 104. For example, rather than utilizing theevent analysis and sensor control platform 102 to peer across to anothersensor device for source data and/or event output confirmation, firstsensor device 103 and second sensor device 104 may peer across to eachother and communicate directly to perform such confirmation/validation.It should also be understood that although the event sequence shownherein depicts a first sensor device 103 and a second sensor device 104,any number of sensor devices may be incorporated into the eventsequence.

FIGS. 3A-3E depict an illustrative event sequence for deploying an eventanalysis and sensor control platform 103 that uses advanced techniquesto perform event analysis and sensor selection in accordance with one ormore example embodiments.

Referring to FIG. 3A, at step 301, the event analysis and sensor controlplatform 102 may access a sensor capability database. In one or moreinstances, in accessing the sensor capability database, the eventanalysis and sensor control platform 102 may determine a plurality ofavailable sensor devices and may determine a plurality of accuracyoutputs, each corresponding to a particular sensor devices ability toaccurately collect a particular type of sensor data (e.g., a first scorefor acceleration accuracy, a second score for breaking detectionaccuracy, or the like). In these instances, the sensor capabilitydatabase may include a manifest and/or configuration that describescapabilities of the various available sensor devices and potentialscenarios in which a subset of the plurality of available sensor devicesmay be used to determine particular types of data under variedconditions.

At step 302, the event analysis and sensor control platform 102 may rankthe available sensor devices, determined at step 301, based on theircorresponding accuracy outputs for each type of source data. Forexample, the event analysis and sensor control platform 102 may generatea first ranked list of available sensor devices based on their accuracyoutputs associated with acceleration data collection and a second rankedlist of available sensor devices based on their accuracy outputsassociated with breaking detection data collection. In one or moreinstances, in ranking the available sensor devices, the event analysisand sensor control platform 102 may determine which of the availablesensor devices most accurately determines each type of data. Forexample, the event analysis and sensor control platform 102 maydetermine that the first sensor device 103 may provide the most accurateacceleration data, whereas the second sensor device 104 may provide themost accurate breaking detection data.

At step 303, the event analysis and sensor control platform 102 mayestablish a connection with the geographic policy database 105. In oneor more instances, in establishing the connection with the geographicpolicy database 105, the event analysis and sensor control platform 102may establish a first wireless data connection with the geographicpolicy database 105 to link the event analysis and sensor controlplatform 102 to the geographic policy database 105.

At step 304, the event analysis and sensor control platform 102 maygenerate and send one or commands directing the geographic policydatabase 105 to determine whether the most accurate sensor device for aparticular type of data, as determined in step 302, complies withgeographic policies regarding sensor data collection in particulargeographic region. For example, use of particular sensors may bepermitted in some geographic regions but not others, and the eventanalysis and sensor control platform 102 may verify whether the mostaccurate sensor device for the particular type of data complies withsuch policies prior to directing the most accurate sensor device tocollect source data. In one or more instances, the event analysis andsensor control platform may send the one or more commands directing thegeographic policy database 105 to determine whether sensor devicescomply with the geographic policies via the communication interface 113and while the first wireless data connection is established. As anexample, the event analysis and sensor control platform 102 may directthe geographic policy database 105 to determine whether the first sensordevice 103 is compliant with geographic policy.

At step 305, the geographic policy database 105 may receive the one ormore commands directing the geographic policy database 105 to determinewhether the sensor devices comply with the geographic policies. In oneor more instances, the geographic policy database 105 may receive theone or more commands directing the geographic policy database 105 todetermine whether the sensor devices comply with the geographic policieswhile the first wireless data connection is established.

Referring to FIG. 3B, at step 306, the geographic policy database 105may determine whether the requested sensor device is compliant withstored geographic policies. In one or more instances, the geographicpolicy database 105 may maintain a stored listing of which sensordevices are non-compliant with geographic policy. In these instances,the geographic policy database 105 may maintain a listing of sensordevices that are not permitted to collect particular source data invarious regions (e.g., state, country, or the like). In these instances,the geographic policy database 105 may compare an identifier of therequested sensor device (e.g., serial number, device type, or the like)to the listing of non-permitted devices, and may determine if datacollection via the requested sensor device complies with geographicpolicies associated with a location of the requested sensor device.

At step 307, the geographic policy database 105 may generate and send anindication of whether the requested sensor device complies with thegeographic policies. In one or more instances, the geographic policydatabase may generate and send the indication of whether the requestedsensor device complies with the geographic policies to the eventanalysis and sensor control platform 102 while the first wireless dataconnection is established.

At step 308, the event analysis and sensor control platform 102 mayreceive the indication of whether the requested sensor device complieswith the geographic policies. In one or more instances, the eventanalysis and sensor control platform 102 may receive the indication ofwhether the requested sensor device complies with the geographicpolicies via the communication interface 113 and while the firstwireless data connection is established. In some instances, the eventanalysis and sensor control platform 102 may determine, based on theindication of whether the requested sensor device complies with thegeographic policies, that the requested sensor device does not complywith the geographic policies. In these instances, the event analysis andsensor control platform 102 may return to step 302 and determine thenext most accurate sensor device on the ranked list of sensor devicesfor the particular data type. In other instances, the event analysis andsensor control platform 102 may determine, based on the indication ofwhether the requested sensor device complies with the geographicpolicies, that the requested sensor device does comply with thegeographic policies. In these instances, the event analysis and sensorcontrol platform 102 may proceed to step 309.

At step 309, the event analysis and sensor control platform 102 mayestablish a connection with the first sensor device 103. In theseinstances, the event analysis and sensor control platform 102 may havepreviously determined that the first sensor device 103 is the mostaccurate sensor device for collection of a particular data type that iscompliant with geographic policies. In one or more instances, the eventanalysis and sensor control platform 102 may establish a second wirelessdata connection with the first sensor device 103 to link the eventanalysis and sensor control platform 102 to the first sensor device 103.

At step 310, the event analysis and sensor control platform 102 maygenerate and send one or more commands directing the first sensor device103 to provide source data. In one or more instances, the event analysisand sensor control platform 102 may send the one or more commands to thefirst sensor device 103 to provide source data via the communicationinterface 113 and while the second wireless data connection isestablished. In these instances, sending the one or more commandsdirecting the first sensor device 103 to provide the source data may beresponsive to determining that the first sensor device complies withgeographic policies based on the indication received at step 308.

At step 311, the event analysis and sensor control platform 102 mayreceive the one or more commands directing the first sensor device 103to provide the source data. In one or more instances, the event analysisand sensor control platform 102 may receive the one or more commandsdirecting the first sensor device 103 to provide the source data whilethe second wireless data connection is established.

Referring to FIG. 3C, at step 312, the first sensor device 103 may sendsource data to the event analysis and sensor control platform 102. Inone or more instances, in sending the source data, the first sensordevice 103 may send telematics data (e.g., acceleration, breakdetection, impact, or the like). Additionally or alternatively, thefirst sensor device 103 may send non-telematics data (e.g., user input,video, audio, images, or the like). In one or more instances, the firstsensor device 103 may have previously collected the source data. Inother instances, the first sensor device 103 might not have previouslycollected the source data, and may collect the source data in responseto receiving the one or more commands directing the first sensor device103 to provide the source data. In some instances, the first sensordevice 103 may send only source data corresponding to the particulardata type which the event analysis and sensor control platform 102selected the first sensor device 103 to provide. In other instances, thefirst sensor device 103 may provide all of the collected source data,regardless of which source data it was selected to provide. In one ormore instances, the first sensor device 103 may send the source data tothe event analysis and sensor control platform 102 while the secondwireless data connection is established.

At step 313, the event analysis and sensor control platform 102 mayreceive the source data from the first sensor device 103. In one or moreinstances, the event analysis and sensor control platform 102 mayreceive the source data from the first sensor device 103 via thecommunication interface 113 and while the second wireless dataconnection is established. In one or more instances, the event analysisand sensor control platform 102 may determine whether additional typesof source data should be analyzed. If so, the event analysis and sensorcontrol platform 102 may return to step 302 to determine a most accuratesensor device for collection of that type source data, and may proceedto determine whether such a sensor device is compliant with geographicpolicies in the manner described above. If not, the event analysis andsensor control platform 102 may proceed to step 314.

At step 314, the event analysis and sensor control platform 102 mayestablish a connection with the second sensor device 104. In theseinstances, the event analysis and sensor control platform 102 may havedetermined that a second type of source data should be analyzed, inaddition to the source data received from the first sensor device 103.In these instances, the event analysis and sensor control platform 102may have determined, via the steps described above, that the secondsensor device 104 is the most accurate source of the second type ofsource data that is compliant with geographic policies. In one or moreinstances, the event analysis and sensor control platform 102 mayestablish a third wireless connection with the second sensor device 104to link the event analysis and sensor control platform 102 to the secondsensor device 104. In one or more instances, the event analysis andsensor control platform 102 may establish connections with multiplesensor devices at substantially the same time. In other instances, theevent analysis and sensor control platform 102 may handle a singlesensor device at a time.

At step 315, the event analysis and sensor control platform 102 maygenerate and send one or more commands directing the second sensordevice 104 to provide source data. In one or more instances, the eventanalysis and sensor control platform 102 may send the one or morecommands directing the second sensor device 104 to provide source datavia the communication interface and while the third wireless dataconnection is established. In one or more instances, in generating theone or more commands directing the second sensor device 104 to providesource data, the event analysis and sensor control platform 102 maygenerate one or more commands directing the second sensor device 104 toprovide different source data than was provided by the first sensordevice 103.

At step 316, the second sensor device 104 may receive the one or morecommands directing the second sensor device 104 to provide the sourcedata. In these instances, the second sensor device may receive the oneor more commands directing the second sensor device 104 to provide thesource data while the third wireless data connection is established.

At step 317, the second sensor device 104 may send the source datarequested at step 316. In one or more instances, in sending the sourcedata, the second sensor device 104 may perform actions similar to thoseperformed by the first sensor device 103 at step 312. However, in theseinstances, the second sensor device 104 may send different source datato the event analysis and sensor control platform 102 than was providedby the first sensor device. In one or more instances, the second sensordevice may send the source data requested at step 316 while the thirdwireless data connection is established.

At step 318, the event analysis and sensor control platform 102 mayreceive the source data sent at step 317. In one or more instances, theevent analysis and sensor control platform 102 may receive the sourcedata via the communication interface 113 and while the third wirelessdata connection is established. In these instances, the event analysisand sensor control platform 102 may receive different source data thanthen source data received at step 313. For example, the event analysisand sensor control platform 102 may have received acceleration data fromthe first sensor device 103, but may receive brake detection data fromthe second sensor device 104. In some instances, steps 314 and 318 mayoccur at substantially the same time as steps 309-309. In otherinstances, they may occur at different times. Once the source data isreceived from the second sensor device 104, the event analysis andsensor control platform 102 may determine whether additional types ofsource data should be collected. If so, the event analysis and sensorcontrol platform may return to step 302. If not, the event analysis andsensor control platform 102 may proceed to step 319.

Referring to FIG. 3D, at step 319, the event analysis and sensor controlplatform 102 may determine a location for event output processing. Inthese instances, the event analysis and sensor control platform 102 maydetermine whether event output processing should be performed at theevent analysis and sensor control platform 102 or locally at one of thesensor devices. In some instances, the event analysis and sensor controlplatform 102 may make this determination based how urgently an eventoutput should be determined. For example, if the source data receivedfrom the first sensor device 103 and second sensor device 104 does notexceed predetermined source data value thresholds, the event analysisand sensor control platform 102 may determine that an event, if oneoccurred, is not likely to need urgent attention. In these instances,the event analysis and sensor control platform 102 may determine thatthe extra time taken to perform the processing at the event analysis andsensor control platform 102 is negligible, and it may perform theprocessing (e.g., proceed to step 326). If the event analysis and sensorcontrol platform 102 determines that one or more of the predeterminedsource data value thresholds are exceeded, the event analysis and sensorcontrol platform 102 may determine that urgent processing should occur,and may proceed to step 320 to initiate local processing on one of thesensor devices. Available processing power at the local sensor devicesmay also be a factor in determination of the location for event outputprocessing by the event analysis and sensor control platform 102. Forexample, the event analysis and sensor control platform 102 maydetermine available processing for the sensor devices and if availableprocessing power does not exceed a predetermined processing thresholdfor any of the sensor devices, the event analysis and sensor controlplatform 102 may determine that it should perform the processing itself.If available processing power does exceed the predetermined processingthreshold for one or more of the sensor devices, the event analysis andsensor control platform 102 might determine that processing should occurlocally at one of the sensor devices.

At step 320, the event analysis and sensor control platform 102 maygenerate a ranked list of the sensor devices and their associatedavailable processing power. In one or more instances, the event analysisand sensor control platform 102 may update the ranked list of sensordevices and their associated available processing power at predeterminedinterfaces, based on software updates, or the like. In the illustrationshown in FIG. 3D, the event analysis and sensor control platform 102 mayhave determined that the first sensor device 103 had more availableprocessing power than the second sensor device 104.

At step 321, the event analysis and sensor control platform 102 maygenerate and send one or more commands directing a sensor device, asreflected in the list at step 320 as having the highest amount ofavailable processing power (e.g., in this illustration, first sensordevice 103), to generate an event output. In these instances, the eventanalysis and sensor control platform 102 may send the one or morecommands directing the first sensor device 103 to generate the eventoutput via the communication interface 113 and while the second wirelessdata connection is established. In one or more instances, the eventanalysis and sensor control platform 102 may send the source datacollected from all of the sensor devices to the first sensor device 103for analysis.

At step 322, the first sensor device 103 may receive the one or morecommands directing the first sensor device 103 to generate the eventoutput. In one or more instances, the first sensor device 103 mayreceive the one or more commands directing the first sensor device 103to generate the event output while the second wireless data connectionis established.

At step 323, the first sensor device 103 may determine an event output.In determining the event output, the first sensor device 103 maydetermine an indication of whether an event occurred (a collision,sudden movement, harsh breaking, rollover, or the like) based on thesource data received from the various data sources. In one or moreinstances, the first sensor device 103 may stich together the sourcedata from the various data sources. Accordingly, the first sensor device103 may compile the most accurate source data corresponding to each datatype, thus resulting in the most accurate depiction of a potential eventscenario (e.g., in contrast to merely receiving all of the source datafrom a particular sensor device regardless of that sensor device'sability to accurately collect and convey the source data). In one ormore instances, the first sensor device 103 may compare the source datareceived to one or more machine learning datasets associated with eventsand non-events (e.g., a non-collision, or the like). In these instances,the machine learning datasets may indicate that particular combinationsof source data are indicative of an event. In these instances, the firstsensor device 103 may determine whether a comparison of the source datato one or more machine learning datasets indicative of an event exceedsa predetermined event threshold. If so, the first sensor device 103 maydetermine that an event occurred. If not, the first sensor device 103may determine that an event did not occur.

Referring to FIG. 3E, at step 324, the first sensor device 103 maygenerate and send an event indication based on the event output. In oneor more instances, the first sensor device 103 may send the eventindication while the second wireless data connection is established.

At step 325, the event analysis and sensor control platform 102 mayreceive the event indication send at step 324. In one or more instances,the event analysis and sensor control platform 102 may receive the eventindication via the communication interface 113 and while the secondwireless data connection is established.

At step 326, the event analysis and sensor control platform 102 maydetermine an event output. In some instances, the event output may havealready been generated by the first sensor device 103. In theseinstances, the event analysis and sensor control platform 102 may derivethe event output from the event indication. In other instances, theevent analysis and sensor control platform 102 may have determined, atstep 319, the processing should be performed by the event analysis andsensor control platform 102. In these instances, the event analysis andsensor control platform 102 may perform actions similar to thoseperformed by the first sensor device 103 at step 323 to determine theevent output.

At step 327, the event analysis and sensor control platform 102 mayestablish a connection with the event assistance platform 106. In one ormore instances, the event analysis and sensor control platform 102 mayestablish a fourth wireless data connection with the event assistanceplatform 106 to link the event analysis and sensor control platform 102to the event assistance platform 106.

At step 328, the event analysis and sensor control platform 102 maygenerate and send an indication of whether or not an event occurred.Actions performed at step 328 may be similar to those described abovewith regard to step 214. In one or more instances, the event analysisand sensor control platform 102 may send the indication of the event viathe communication interface 113 and while the fourth wireless dataconnection is established.

At step 329, the event assistance platform 106 may receive theindication of the event. In one or more instances, the event assistanceplatform 106 may receive the indication of the event while the fourthwireless data connection is established. Actions performed at step 329may be similar to those described above with regard to step 215.

Subsequently the event sequence may end. It should be understood thatthe methods described in FIGS. 3A-3E may be performed in addition to, orindependently of, the methods described in FIGS. 2A-3C. It should alsobe understood that although the first sensor device 103 and the secondsensor device 104 are shown, any number of sensor devices may beimplemented in these methods.

FIG. 4 depicts an illustrative method for deploying an event analysisand sensor control platform 103 that uses advanced techniques to performevent analysis and sensor selection in accordance with one or moreexample embodiments. Referring to FIG. 4, at step 405, the computingplatform may establish a connection to a first sensor device. At step410, the computing platform may determine whether the first sensordevice is peering directly to a second sensor device or whether thefirst sensor device is peering through the computing platform itself. Ifthe first sensor device is peering directly to the second sensor device,the computing platform may proceed to step 445. If the first sensordevice is peering through the computing platform, the computing platformmay proceed to step 415.

At step 415, the computing platform may receive first source data fromthe first sensor device. At step 420, the computing platform maydetermine an event output based on the first source data. At step 425,the computing platform may establish a connection with a second sensordevice. At step 430, the computing platform may generate and send one ormore commands directing the second sensor device to confirm the eventoutput. At step 435, the computing platform may receive second sourcedata and/or a second event output. At step 440, the computing platformmay compare the received second source data and/or second event outputwith the first source data and first event output. At step 455, thecomputing platform may determine whether a confirmation threshold wasexceed based on the comparison at step 440. If the confirmationthreshold was exceeded, the computing platform may proceed to step 465.If the confirmation threshold was not exceeded, the computing platformmay proceed to step 460. At step 460, the confirmation threshold mayupdate the machine learning engine used to determine the event output.

Returning to step 410, if the first sensor device is directly peering tothe second sensor device, the computing platform may proceed to step445. At step 445, the computing platform may receive source data fromthe first sensor device, the second sensor device, or both. At step 450,the computing platform may determine the event output based on thesource data received at step 445.

At step 465, the computing platform may determine whether an event wasdetermined based on the event output. If an event was determined, thecomputing platform may proceed to step 470. If an event was notdetermined, the method may end.

At step 470, the computing platform may establish a connection with anevent assistance platform. At step 475, the computing platform may sendan event indication to the event assistance platform.

FIG. 5 depicts an illustrative method for deploying an event analysisand sensor control platform 103 that uses advanced techniques to performevent analysis and sensor selection in accordance with one or moreexample embodiments. At step 505, the computing platform may access asensor capability database. At step 510, the computing platform may rankavailable sensor devices based on their capability to collect particulartypes of source data. At step 515, the computing platform may establisha connection with a geographic policy database. At step 520, thecomputing platform may send one or more commands directing thegeographic policy database to determine whether a ranked sensor deviceis compliant with geographic policies. At step 525, the computingplatform may receive an indication of whether or not the sensor deviceis compliant with the geographic policies. At step 530, the computingplatform may determine, based on the indication of whether or not thesensor device is compliant with the geographic policies, whether thesensor device is compliant. If the sensor device is not compliant, thecomputing platform may return to step 520. If the sensor device iscompliant, the computing platform may proceed to step 535.

At step 535, the computing platform may establish a connection with thesensor device. At step 540, the computing platform may send one or morecommands directing the sensor device to provide source data. At step545, the computing platform may receive the source data from the sensordevice. At step 550, the computing platform may determine whether anadditional data type is requested. If another data type is requested,the computing platform may return to step 510. If another data type isnot requested, the computing platform may proceed to step 555.

At step 555, the computing platform may determine whether the sensordevice is to determine an event or whether the computing platform is tomake the determination. If the computing platform is to make thatdetermination, the computing platform may proceed to step 575. If thesensor device is to make that determination, the computing platform mayproceed to step 560. At step 560, the computing platform may rank thesensor devices based on their available processing power. At step 565,the computing platform may send one or more commands directing thehighest ranked sensor device to determine whether an event occurred. Atstep 570, the computing platform may receive an event indication fromthe sensor device. At step 575, the computing platform may determine,based on the event indication, whether an event was determined. If so,the computing platform may proceed to step 580. If not, the method mayend.

At step 580, the computing platform may establish a connection with anevent assistance platform. At step 585, the computing platform may sendan indication to the event assistance platform that an event occurred.

One or more aspects of the disclosure may be embodied in computer-usabledata or computer-executable instructions, such as in one or more programmodules, executed by one or more computers or other devices to performthe operations described herein. Generally, program modules includeroutines, programs, objects, components, data structures, and the likethat perform particular tasks or implement particular abstract datatypes when executed by one or more processors in a computer or otherdata processing device. The computer-executable instructions may bestored as computer-readable instructions on a computer-readable mediumsuch as a hard disk, optical disk, removable storage media, solid-statememory, RAM, and the like. The functionality of the program modules maybe combined or distributed as desired in various embodiments. Inaddition, the functionality may be embodied in whole or in part infirmware or hardware equivalents, such as integrated circuits,application-specific integrated circuits (ASICs), field programmablegate arrays (FPGA), and the like. Particular data structures may be usedto more effectively implement one or more aspects of the disclosure, andsuch data structures are contemplated to be within the scope of computerexecutable instructions and computer-usable data described herein.

Various aspects described herein may be embodied as a method, anapparatus, or as one or more computer-readable media storingcomputer-executable instructions. Accordingly, those aspects may takethe form of an entirely hardware embodiment, an entirely softwareembodiment, an entirely firmware embodiment, or an embodiment combiningsoftware, hardware, and firmware aspects in any combination. Inaddition, various signals representing data or events as describedherein may be transferred between a source and a destination in the formof light or electromagnetic waves traveling through signal-conductingmedia such as metal wires, optical fibers, or wireless transmissionmedia (e.g., air or space). In general, the one or morecomputer-readable media may be and/or include one or more non-transitorycomputer-readable media.

As described herein, the various methods and acts may be operativeacross one or more computing servers and one or more networks. Thefunctionality may be distributed in any manner, or may be located in asingle computing device (e.g., a server, a client computer, and thelike). For example, in alternative embodiments, one or more of thecomputing platforms discussed above may be combined into a singlecomputing platform, and the various functions of each computing platformmay be performed by the single computing platform. In such arrangements,any and/or all of the above-discussed communications between computingplatforms may correspond to data being accessed, moved, modified,updated, and/or otherwise used by the single computing platform.Additionally or alternatively, one or more of the computing platformsdiscussed above may be implemented in one or more virtual machines thatare provided by one or more physical computing devices. In sucharrangements, the various functions of each computing platform may beperformed by the one or more virtual machines, and any and/or all of theabove-discussed communications between computing platforms maycorrespond to data being accessed, moved, modified, updated, and/orotherwise used by the one or more virtual machines.

Aspects of the disclosure have been described in terms of illustrativeembodiments thereof. Numerous other embodiments, modifications, andvariations within the scope and spirit of the appended claims will occurto persons of ordinary skill in the art from a review of thisdisclosure. For example, one or more of the steps depicted in theillustrative figures may be performed in other than the recited order,and one or more depicted steps may be optional in accordance withaspects of the disclosure.

What is claimed is:
 1. A computing platform comprising: at least oneprocessor; a communication interface communicatively coupled to the atleast one processor; and memory storing computer-readable instructionsthat, when executed by the processor, cause the computing platform to:access a sensor capability database to determine an accuracy outputassociated with each of a plurality of sensor devices for each of aplurality of data types; rank, for each of the data types and based ontheir accuracy outputs, the plurality of sensor devices, resulting in aranked list of the plurality of sensor devices; send one or morecommands directing a first sensor device to provide first source dataand directing a second sensor device to provide second source data,wherein the first sensor device is ranked highest on the ranked list ofthe plurality of sensor devices for a data type corresponding to thefirst source data and wherein the second sensor device is ranked higheston the ranked list of the plurality of sensor devices for a data typecorresponding to the second source data; receive, from the first sensordevice and the second sensor device respectively, the first source dataand the second source data; and generate, based on the first source dataand the second source data, an event output indicating whether a vehicleassociated with the first source data and the second source dataexperienced an event.
 2. The computing platform of claim 1, wherein thememory stores additional computer-readable instructions that, whenexecuted by the at least one processor, further cause the computingplatform to: establish a wireless connection with a geographic policydatabase; send, while the wireless connection is established and afterranking the plurality of sensor devices, one or more commands directingthe geographic policy database to provide an indication of whether useof the first sensor device complies with geographic policies; andreceive, while the wireless connection is established, the indication ofwhether use of the first sensor device complies with geographicpolicies.
 3. The computing platform of claim 2, wherein sending the oneor more commands directing the first sensor device to provide firstsource data is in response to determining, based on the indication ofwhether the use of the first sensor device complies with geographicpolicies, that the first sensor device complies with geographicpolicies.
 4. The computing platform of claim 2, wherein the memorystores additional computer-readable instructions that, when executed bythe at least one processor, further cause the platform to: send, whilethe wireless connection is established and after ranking the pluralityof sensor devices, one or more commands directing the geographic policydatabase to provide an indication of whether use of a third sensordevice complies with geographic policies, wherein the third sensordevice is ranked highest on the ranked list of the plurality of sensordevices for a data type corresponding to third source data; receive,while the wireless connection is established, the indication of whetheruse of the third sensor device complies with geographic policies;determine, based on the indication of whether use of the third sensordevice complies with geographic policies, that the third sensor deviceis non-compliant with the geographic policies; send, after determiningthat the third sensor device is non-compliant with the geographicpolicies, one or more commands directing the geographic policy databaseto provide an indication of whether use of a fourth sensor devicecomplies with geographic policies, wherein the fourth sensor device isranked second highest on the ranked list of the plurality of sensordevices for the data type corresponding to the third source data; andsend, in response to determining, based on the indication of whether theuse of the third sensor device complies with geographic policies, thatthe third sensor device complies with geographic policies, one or morecommands directing the fourth sensor device to provide the third sourcedata.
 5. The computing platform of claim 2, wherein the memory storesadditional computer-readable instructions that, when executed by the atleast one processor, further cause the computing platform to: determinethat event analysis should occur locally at one of the plurality ofsensor devices; rank the plurality of sensor devices based on availableprocessing power at each of the plurality of sensor devices, resultingin a ranked list of sensor devices by processing power; and send one ormore commands to the first sensor device directing the first sensordevice to determine the event output, wherein the first sensor device isthe highest ranked device on the ranked list of sensor devices byprocessing power.
 6. The computing platform of claim 2, wherein thememory stores additional computer-readable instructions that, whenexecuted by the at least one processor, further cause the computingplatform to determine that event analysis should occur at the computingplatform.
 7. The computing device of claim 6, wherein the determiningthe event output is in response to determining that the event analysisshould occur at the computing platform.
 8. The computing device of claim7, wherein determining the event output comprises determining, using oneor more machine learning algorithms and one or more machine learningdatasets, an indication of whether the vehicle experienced an event. 9.The computing device of claim 1, wherein the memory stores additionalcomputer-readable instructions that, when executed by the at least oneprocessor, further cause the computing platform to: establish a wirelessconnection with an event assistance platform; and send, while thewireless connection is established and to the event assistance platform,the event output and one or more commands directing the event assistanceplatform to cause display of the event output.
 10. A method comprising:at a computing platform comprising at least one processor, acommunication interface, and memory: accessing a sensor capabilitydatabase to determine an accuracy output associated with each of aplurality of sensor devices for each of a plurality of data types;ranking, for each of the data types and based on their accuracy outputs,the plurality of sensor devices, resulting in a ranked list of theplurality of sensor devices; sending one or more commands directing afirst sensor device to provide first source data and directing a secondsensor device to provide second source data, wherein the first sensordevice is ranked highest on the ranked list of the plurality of sensordevices for a data type corresponding to the first source data andwherein the second sensor device is ranked highest on the ranked list ofthe plurality of sensor devices for a data type corresponding to thesecond source data; receiving, from the first sensor device and thesecond sensor device respectively, the first source data and the secondsource data; and generating, based on the first source data and thesecond source data, an event output indicating whether a vehicleassociated with the first source data and the second source dataexperienced an event.
 11. The method of claim 10, further comprising:establishing a wireless connection with a geographic policy database;sending, while the wireless connection is established and after rankingthe plurality of sensor devices, one or more commands directing thegeographic policy database to provide an indication of whether use ofthe first sensor device complies with geographic policies; andreceiving, while the wireless connection is established, the indicationof whether use of the first sensor device complies with geographicpolicies.
 12. The method of claim 11, wherein sending the one or morecommands directing the first sensor device to provide first source datais in response to determining, based on the indication of whether theuse of the first sensor device complies with geographic policies, thatthe first sensor device complies with geographic policies.
 13. Themethod of claim 11, further comprising: sending, while the wirelessconnection is established and after ranking the plurality of sensordevices, one or more commands directing the geographic policy databaseto provide an indication of whether use of a third sensor devicecomplies with geographic policies, wherein the third sensor device isranked highest on the ranked list of the plurality of sensor devices fora data type corresponding to third source data; receiving, while thewireless connection is established, the indication of whether use of thethird sensor device complies with geographic policies; determining,based on the indication of whether use of the third sensor devicecomplies with geographic policies, that the third sensor device isnon-compliant with the geographic policies; sending, after determiningthat the third sensor device is non-compliant with the geographicpolicies, one or more commands directing the geographic policy databaseto provide an indication of whether use of a fourth sensor devicecomplies with geographic policies, wherein the fourth sensor device isranked second highest on the ranked list of the plurality of sensordevices for the data type corresponding to the third source data; andsending, in response to determining, based on the indication of whetherthe use of the third sensor device complies with geographic policies,that the third sensor device complies with geographic policies, one ormore commands directing the fourth sensor device to provide the thirdsource data.
 14. The method of claim 11, further comprising: determiningthat event analysis should occur locally at one of the plurality ofsensor devices; ranking the plurality of sensor devices based onavailable processing power at each of the plurality of sensor devices,resulting in a ranked list of sensor devices by processing power; andsending one or more commands to the first sensor device directing thefirst sensor device to determine the event output, wherein the firstsensor device is the highest ranked device on the ranked list of sensordevices by processing power.
 15. The method of claim 11, furthercomprising determining that event analysis should occur at the computingplatform.
 16. The method of claim 15, wherein the determining the eventoutput is in response to determining that the event analysis shouldoccur at the computing platform.
 17. The method of claim 16, whereindetermining the event output comprises determining, using one or moremachine learning algorithms and one or more machine learning datasets,an indication of whether the vehicle experienced an event.
 18. Themethod of claim 10, further comprising: establishing a wirelessconnection with an event assistance platform; and sending, while thewireless connection is established and to the event assistance platform,the event output and one or more commands directing the event assistanceplatform to cause display of the event output.
 19. One or morenon-transitory computer-readable media storing instructions that, whenexecuted by a computing platform comprising at least one processor, acommunication interface, and memory, cause the computing platform to:access a sensor capability database to determine an accuracy outputassociated with each of a plurality of sensor devices for each of aplurality of data types; rank, for each of the data types and based ontheir accuracy outputs, the plurality of sensor devices, resulting in aranked list of the plurality of sensor devices; send one or morecommands directing a first sensor device to provide first source dataand directing a second sensor device to provide second source data,wherein the first sensor device is ranked highest on the ranked list ofthe plurality of sensor devices for a data type corresponding to thefirst source data and wherein the second sensor device is ranked higheston the ranked list of the plurality of sensor devices for a data typecorresponding to the second source data; receive, from the first sensordevice and the second sensor device respectively, the first source dataand the second source data; and generate, based on the first source dataand the second source data, an event output indicating whether a vehicleassociated with the first source data and the second source dataexperienced an event.
 20. The one or more non-transitorycomputer-readable media of claim 19, wherein the memory storesadditional instructions that, when executed by the one or moreprocessors, cause the computing platform to: establish a wirelessconnection with a geographic policy database; send, while the wirelessconnection is established and after ranking the plurality of sensordevices, one or more commands directing the geographic policy databaseto provide an indication of whether use of the first sensor devicecomplies with geographic policies; and receive, while the wirelessconnection is established, the indication of whether use of the firstsensor device complies with geographic policies.